An efficient synthesis of mono-, di-, and tri-substituted 1,3-thiazoles employing functionalized thioamides as thiocarbonyl precursors.

Herein, we report an efficient strategy to synthesize functionalized 1,3-thiazoles using alkyl 2-amino-2-thioxoacetates. Thioamides, the synthetic precursors, react effortlessly with electrophilic reagents and are transformed into a series of phenyl-, methyl-, and acyl-substituted thiazoles with high functionalization at the 2nd position through sequential C-S/C-N bond formation. Rapid reaction times under metal-free mild conditions is a noteworthy feature of the reported protocol. Given the intriguing biological significance of the synthesized molecules, we further performed a comprehensive evaluation of their potency against the SARS-CoV-2 receptor (PDB ID: 7mc6) using a molecular docking approach, with binding scores ranging from -4.3 to -8.2 kcal mol-1.

Unraveling the crystal structure, stability and drug likeness of 1,3,4-oxadiazole derivatives against Myelofibrosis: a combined experimental and computational investigation.

Herein, we report the synthesis and characterization of novel 1,3,4-oxadiazole derivatives, 2-methoxybenzyl 5-(4-chlorophenyl)-1,3,4-oxadiazole-2-carboxylate (C1) 2-methoxybenzyl 5-(2-chlorophenyl)-1,3,4-oxadiazole-2-carboxylate (C2), and methoxybenzyl 5-(3-chlorophenyl)-1,3,4-oxadiazole-2-carboxylate (C3) obtained through desulfurative cyclization reaction. The compound C2 was crystallized, and its crystal structure was elucidated using single-crystal X-ray diffraction technique. The Hirshfeld surface analysis was carried out to analyze, visualize and globally appreciate the weak interactions involved in crystal packing. These analyses were complemented by Quantum Theory of Atoms In Molecules (QTAIM) and Reduced Density Gradient (RDG), which allowed us to decipher the nature and types of attractive forces that contribute to maintain the crystal structure of the titled compound. Moreover, the ADME profile of the compound was predicted to assess its drug likeness. Finally, in silico studies were performed to explore the binding affinity of the compounds (C1-3) against Myelofibrosis through molecular docking and molecular dynamic simulations.Communicated by Ramaswamy H. Sarma.

Regioselective Synthesis of 2,5-Disubstituted-1,3,4-thiadiazoles and 1,3,4-Oxadiazoles via Alkyl 2-(Methylthio)-2-thioxoacetates and Alkyl 2-Amino-2-thioxoacetates.

An acid-catalyzed regioselective cyclization reaction of 2,5-disubstituted-1,3,4-thiadiazoles and 1,3,4-oxadiazoles has been developed. The synthetic precursors alkyl 2-(methylthio)-2-thioxoacetates/alkyl 2-amino-2-thioxoacetates react efficiently with acyl hydrazides, which transformed into a series of dehydrative and desulfurative products with employment of p-TSA and AcOH through a regioselective cyclization process. The alkyl 2-amino-2-thioxoacetate pathway generates excellent yield among the mentioned procedures. The reported methods are operationally simplistic and highly efficient with metal-free conditions and demonstrate significant functional group compatibility. Regioselective cyclized products were confirmed by single-crystal X-ray diffraction studies.

Emerging Technologies, STI Diaspora and Science Diplomacy in India: Towards a New Approach.

Utilizing the expertise and knowledge resources of the diaspora, particularly the scientific diaspora, has been part of the strategies of many countries. In the recent years, realizing the importance of the potential of the diaspora to contribute to national development and Science, Technology, and Innovation ecosystem, countries have used Science Diplomacy also to engage with the scientific diaspora. Science Diplomacy is hailed as an enabler and facilitator and is often seen in the context of international S&T collaboration or big science projects. But the use of Science Diplomacy for diaspora engagement calls for specific strategies and meaningful initiatives. India is one of the major developing countries that has given a major thrust to engaging with the scientific diaspora. India is also a leading player in the global Science Diplomacy arena. This article critically examines India's initiatives and strategies for engagement with the scientific diaspora. It points out that the Science Diplomacy dimension is missing in this. Using examples from other countries, recent thinking, and developments in Science Diplomacy, this study outlines an approach with some examples of strategies and initiatives for harnessing Science Diplomacy to enhance engagement with the scientific diaspora and create a win-win milieu for India and the diaspora. The approach takes into account the proposed and ongoing initiatives in emerging technologies in India, including quantum technologies and Artificial Intelligence. Such a framework will create a synergy among various programs and initiatives by using Science Diplomacy as a facilitator and catalyst. Under this framework, Diaspora is involved not only as experts and contributors to scientific advancements but also as stakeholders. This dual role of the STI Diaspora can bring a paradigm shift in traditional understanding and use of science diplomacy, particularly to engage and harness the potential of the STI Diaspora for Sustainable Development.

Emotional Semantics-Preserved and Feature-Aligned CycleGAN for Visual Emotion Adaptation.

Thanks to large-scale labeled training data, deep neural networks (DNNs) have obtained remarkable success in many vision and multimedia tasks. However, because of the presence of domain shift, the learned knowledge of the well-trained DNNs cannot be well generalized to new domains or datasets that have few labels. Unsupervised domain adaptation (UDA) studies the problem of transferring models trained on one labeled source domain to another unlabeled target domain. In this article, we focus on UDA in visual emotion analysis for both emotion distribution learning and dominant emotion classification. Specifically, we design a novel end-to-end cycle-consistent adversarial model, called CycleEmotionGAN++. First, we generate an adapted domain to align the source and target domains on the pixel level by improving CycleGAN with a multiscale structured cycle-consistency loss. During the image translation, we propose a dynamic emotional semantic consistency loss to preserve the emotion labels of the source images. Second, we train a transferable task classifier on the adapted domain with feature-level alignment between the adapted and target domains. We conduct extensive UDA experiments on the Flickr-LDL and Twitter-LDL datasets for distribution learning and ArtPhoto and Flickr and Instagram datasets for emotion classification. The results demonstrate the significant improvements yielded by the proposed CycleEmotionGAN++ compared to state-of-the-art UDA approaches.

A Review of Single-Source Deep Unsupervised Visual Domain Adaptation.

Large-scale labeled training datasets have enabled deep neural networks to excel across a wide range of benchmark vision tasks. However, in many applications, it is prohibitively expensive and time-consuming to obtain large quantities of labeled data. To cope with limited labeled training data, many have attempted to directly apply models trained on a large-scale labeled source domain to another sparsely labeled or unlabeled target domain. Unfortunately, direct transfer across domains often performs poorly due to the presence of domain shift or dataset bias. Domain adaptation (DA) is a machine learning paradigm that aims to learn a model from a source domain that can perform well on a different (but related) target domain. In this article, we review the latest single-source deep unsupervised DA methods focused on visual tasks and discuss new perspectives for future research. We begin with the definitions of different DA strategies and the descriptions of existing benchmark datasets. We then summarize and compare different categories of single-source unsupervised DA methods, including discrepancy-based methods, adversarial discriminative methods, adversarial generative methods, and self-supervision-based methods. Finally, we discuss future research directions with challenges and possible solutions.

Why Public Engagement Matters in Science.

Despite criticisms, public engagement is a necessary part of the process to democratize science. Organizations such as the US National Academy of Sciences (NAS) and the Organization for Economic Cooperation and Development (OECD) have recognized its importance. Citizen science and stakeholder involvement in medical research demonstrate that the public is not always a passive beneficiary of science and can contribute to it.

Biobanking and Privacy in India.

Biobank-based research is not specifically addressed in Indian statutory law and therefore Indian Council for Medical Research guidelines are the primary regulators of biobank research in India. The guidelines allow for broad consent and for any level of identification of specimens. Although privacy is a fundamental right under the Indian Constitution, courts have limited this right when it conflicts with other rights or with the public interest. Furthermore, there is no established privacy test or actionable privacy right in the common law of India. In order to facilitate biobank-based research, both of these lacunae should be addressed by statutory law specifically addressing biobanking and more directly addressing the accompanying privacy concerns. A biobank-specific law should be written with international guidelines in mind, but harmonization with other laws should not be attempted until after India has created a law addressing biobank research within the unique legal and cultural environment of India.

Role of Ki-67 labeling index as an adjunct to the histopathological diagnosis and grading of astrocytomas.

AIM OF THE STUDY: Ki-67 labeling index (LI) is used in the assessment of cell proliferating activity. It has been widely documented for various human tumors, including the brain neoplasms. The aim of the present study is to evaluate Ki-67 as proliferative index in the grading of astrocytomas in order to predict the biological behavior of the tumor and prognosis of patients. MATERIALS AND METHODS: In the present study, a total of 105 patients with astrocytomas were included. Ki-67 LI was done on all the astrocytomas and was compared in correlation with World Health Organization histological grading of astrocytomas. RESULTS: The mean Ki-67 LI in Grade I astrocytomas was 3.36 ± 4.59 standard deviation (SD), 7.05 ± 4.16 SD in Grade II astrocytomas, 28.24 ± 6.23 SD in Grade III astrocytomas and 38.7 ± 7.19 SD in Grade IV astrocytomas. P values were significant between all grades of astrocytomas except between Grade I and Grade II tumors which was 0.5076. CONCLUSIONS: Assessment of astrocytic tumor proliferative potential provides important prognostic information that supplements standard histological grading. Ki-67 LI is the simplest and most reliable methods of all. This study demonstrates that, Ki-67 LI serves as an important prognostic marker in human astrocytomas. Ki-67 LI solely correlates with a grade of the tumor. Average level of Ki-67 LI varies between different grades of astrocytic tumors but some overlap of values does exist.